Articles | Volume 17, issue 6
https://doi.org/10.5194/essd-17-2535-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-17-2535-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description article
| 
12 Jun 2025
Data description article |
| 12 Jun 2025
| 12 Jun 2025
GloUCP: a global 1 km spatially continuous urban canopy parameters for the WRF model
Weilin Liao
Guangdong Key Laboratory for Urbanization and Geo-simulation, School of Geography and Planning, Sun Yat-sen University, Guangzhou, 510275, China
Key Laboratory of Urban Meteorology, China Meteorological Administration, Beijing, 100089, China
Yanman Li
Guangdong Key Laboratory for Urbanization and Geo-simulation, School of Geography and Planning, Sun Yat-sen University, Guangzhou, 510275, China
Xiaoping Liu
CORRESPONDING AUTHOR
Guangdong Key Laboratory for Urbanization and Geo-simulation, School of Geography and Planning, Sun Yat-sen University, Guangzhou, 510275, China
Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, 519082, China
Yuhao Wang
Guangdong Key Laboratory for Urbanization and Geo-simulation, School of Geography and Planning, Sun Yat-sen University, Guangzhou, 510275, China
Yangzi Che
Guangdong Key Laboratory for Urbanization and Geo-simulation, School of Geography and Planning, Sun Yat-sen University, Guangzhou, 510275, China
Ledi Shao
Guangdong Key Laboratory for Urbanization and Geo-simulation, School of Geography and Planning, Sun Yat-sen University, Guangzhou, 510275, China
Guangzhao Chen
Guangdong Key Laboratory for Urbanization and Geo-simulation, School of Geography and Planning, Sun Yat-sen University, Guangzhou, 510275, China
Hua Yuan
Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, 519082, China
School of Atmospheric Sciences, Sun Yat-sen University, Guangzhou, 510275, China
Ning Zhang
School of Atmospheric Sciences, Nanjing University, Nanjing, 210023, China
Fei Chen
Division of Environment and Sustainability, The Hong Kong University of Science and Technology, Hong Kong SAR, 999077, China
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Cited
12 citations as recorded by crossref.
- Effects of urban canopy on kinematic and boundary layer structures of the landfalling Typhoon Lekima (2019) X. Ao et al. https://doi.org/10.1016/j.uclim.2026.102859
- Unraveling the intractable trilemma in urban weather and climate modeling P. Li et al. https://doi.org/10.1038/s42949-026-00388-z
- Assessing the urban heat-energy nexus through morphology-specific cooling demand during an extreme heatwave X. Li et al. https://doi.org/10.1016/j.energy.2026.142134
- Linking urban population exposure to heatwaves with land cover change across the UK Y. Sun et al. https://doi.org/10.1016/j.scs.2026.107349
- Impacts of urban morphology and sky conditions on microscale surface and canopy heat islands under subtropical climate: Scaled outdoor experiments G. Chen et al. https://doi.org/10.1016/j.buildenv.2026.114636
- Leveraging automated machine learning (AutoML) for urban climate emulation J. Yu et al. https://doi.org/10.1016/j.bdes.2025.100040
- Spatiotemporal linkage and transmission of urban heat islands in the Yangtze River Delta urban agglomeration: the role of urban heat advection J. Xue et al. https://doi.org/10.5194/acp-26-11543-2026
- Dynamic parameterization of global land surface albedo components: Bare soil, non-photosynthetic vegetation, and photosynthetic vegetation A. Jia et al. https://doi.org/10.1016/j.rse.2025.114943
- Convolution neural network-based estimation of high-resolution urban canopy parameters for urban climate modelling K. Gupta et al. https://doi.org/10.1016/j.uclim.2026.103098
- Mapping the aerodynamic parameters for built environment: A CFD simulation and machine learning framework J. Chen & Z. Mo https://doi.org/10.1016/j.buildenv.2026.114804
- Mapping drag coefficient using CFD and machine learning with application to urban canopy model J. Chen et al. https://doi.org/10.1016/j.scs.2025.106719
- Representation of global mega-cities and their urban heat island in CORDEX-CORE regional climate model simulations G. Langendijk et al. https://doi.org/10.1038/s42949-025-00325-6
12 citations as recorded by crossref.
- Effects of urban canopy on kinematic and boundary layer structures of the landfalling Typhoon Lekima (2019) X. Ao et al. https://doi.org/10.1016/j.uclim.2026.102859
- Unraveling the intractable trilemma in urban weather and climate modeling P. Li et al. https://doi.org/10.1038/s42949-026-00388-z
- Assessing the urban heat-energy nexus through morphology-specific cooling demand during an extreme heatwave X. Li et al. https://doi.org/10.1016/j.energy.2026.142134
- Linking urban population exposure to heatwaves with land cover change across the UK Y. Sun et al. https://doi.org/10.1016/j.scs.2026.107349
- Impacts of urban morphology and sky conditions on microscale surface and canopy heat islands under subtropical climate: Scaled outdoor experiments G. Chen et al. https://doi.org/10.1016/j.buildenv.2026.114636
- Leveraging automated machine learning (AutoML) for urban climate emulation J. Yu et al. https://doi.org/10.1016/j.bdes.2025.100040
- Spatiotemporal linkage and transmission of urban heat islands in the Yangtze River Delta urban agglomeration: the role of urban heat advection J. Xue et al. https://doi.org/10.5194/acp-26-11543-2026
- Dynamic parameterization of global land surface albedo components: Bare soil, non-photosynthetic vegetation, and photosynthetic vegetation A. Jia et al. https://doi.org/10.1016/j.rse.2025.114943
- Convolution neural network-based estimation of high-resolution urban canopy parameters for urban climate modelling K. Gupta et al. https://doi.org/10.1016/j.uclim.2026.103098
- Mapping the aerodynamic parameters for built environment: A CFD simulation and machine learning framework J. Chen & Z. Mo https://doi.org/10.1016/j.buildenv.2026.114804
- Mapping drag coefficient using CFD and machine learning with application to urban canopy model J. Chen et al. https://doi.org/10.1016/j.scs.2025.106719
- Representation of global mega-cities and their urban heat island in CORDEX-CORE regional climate model simulations G. Langendijk et al. https://doi.org/10.1038/s42949-025-00325-6
Saved (final revised paper)
Latest update: 14 Sep 2026
Short summary
The currently available urban canopy parameter (UCP) datasets are limited to just a few cities for urban climate simulations by the Weather Research and Forecasting (WRF) model. To address this gap, we develop a global 1 km spatially continuous UCP dataset (GloUCP) which provides superior spatial coverage and higher accuracy in capturing urban morphology across diverse regions. It has great potential to support further advancements in urban climate modeling and related applications.
The currently available urban canopy parameter (UCP) datasets are limited to just a few cities...
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